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      Socioeconomic gradients in the effects of universal school-based health behaviour interventions: a systematic review of intervention studies

      research-article
      , , , ,
      BMC Public Health
      BioMed Central

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          Abstract

          Background

          Socioeconomic inequalities in health behaviour emerge in early life before tracking into adulthood. Many interventions to improve childhood health behaviours are delivered via schools, often targeting poorer areas. However, targeted approaches may fail to address inequalities within more affluent schools. Little is known about types of universal school-based interventions which make inequalities better or worse.

          Methods

          Seven databases were searched using a range of natural language phrases, to identify trials and quasi-experimental evaluations of universal school-based interventions focused on smoking, alcohol, diet and/or physical activity, published from 2008–14. Articles which examined differential effects by socioeconomic status ( N = 20) were synthesised using harvest plot methodology. Content analysis of 98 intervention studies examined potential reasons for attention or inattention to effects on inequality.

          Results

          Searches identified approximately 12,000 hits. Ninety-eight evaluations were identified, including 90 completed studies, of which 20 reported effects on SES inequality. There were substantial geographical biases in reporting of inequality, with only 1 of 23 completed North American studies testing differential effects, compared to 15 out of 52 completed European studies. Studies reported a range of positive, neutral or negative SES gradients in effects. All studies with a negative gradient in effect (i.e. which widened inequality) included educational components alone or in combination with environmental change or family involvement. All studies with positive gradients in effects included environmental change components, alone or combined with education. Effects of multi-level interventions on inequality were inconsistent. Content analyses indicated that in approximately 1 in 4 studies SES inequalities were discussed in defining the problem or rationale for intervention. Other potential barriers to testing effect on inequality included assumptions that universal delivery guaranteed universal effect, or that interventions would work better for poorer groups because they had most to gain.

          Conclusions

          Universal school-based interventions may narrow, widen or have no effect on inequality. There is a significant need for more routine testing of the effects of such interventions on inequality to enable firmer conclusions regarding types of interventions which affect inequality.

          PROSPERO registration number

          CRD42014014548

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12889-015-2244-x) contains supplementary material, which is available to authorized users.

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          Most cited references45

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          Translating social ecological theory into guidelines for community health promotion.

          D Stokols (2015)
          Health promotion programs often lack a clearly specified theoretical foundation or are based on narrowly conceived conceptual models. For example, lifestyle modification programs typically emphasize individually focused behavior change strategies, while neglecting the environmental underpinnings of health and illness. This article compares three distinct, yet complementary, theoretical perspectives on health promotion: behavioral change, environmental enhancement, and social ecological models. Key strengths and limitations of each perspective are examined, and core principles of social ecological theory are used to derive practical guidelines for designing and evaluating community health promotion programs. Directions for future health promotion research are discussed, including studies examining the role of intermediaries (e.g., corporate decision-makers, legislators) in promoting the well-being of others, and those evaluating the duration and scope of intervention outcomes.
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            • Record: found
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            The harvest plot: A method for synthesising evidence about the differential effects of interventions

            Background One attraction of meta-analysis is the forest plot, a compact overview of the essential data included in a systematic review and the overall 'result'. However, meta-analysis is not always suitable for synthesising evidence about the effects of interventions which may influence the wider determinants of health. As part of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking, we designed a novel approach to synthesis intended to bring aspects of the graphical directness of a forest plot to bear on the problem of synthesising evidence from a complex and diverse group of studies. Methods We coded the included studies (n = 85) on two methodological dimensions (suitability of study design and quality of execution) and extracted data on effects stratified by up to six different dimensions of inequality (income, occupation, education, gender, race or ethnicity, and age), distinguishing between 'hard' (behavioural) and 'intermediate' (process or attitudinal) outcomes. Adopting a hypothesis-testing approach, we then assessed which of three competing hypotheses (positive social gradient, negative social gradient, or no gradient) was best supported by each study for each dimension of inequality. Results We plotted the results on a matrix ('harvest plot') for each category of intervention, weighting studies by the methodological criteria and distributing them between the competing hypotheses. These matrices formed part of the analytical process and helped to encapsulate the output, for example by drawing attention to the finding that increasing the price of tobacco products may be more effective in discouraging smoking among people with lower incomes and in lower occupational groups. Conclusion The harvest plot is a novel and useful method for synthesising evidence about the differential effects of population-level interventions. It contributes to the challenge of making best use of all available evidence by incorporating all relevant data. The visual display assists both the process of synthesis and the assimilation of the findings. The method is suitable for adaptation to a variety of questions in evidence synthesis and may be particularly useful for systematic reviews addressing the broader type of research question which may be most relevant to policymakers.
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              A typology of actions to tackle social inequalities in health.

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                Author and article information

                Contributors
                02920879609 , MooreG@cardiff.ac.uk
                LittlecottH@cardiff.ac.uk
                TurleyRL@cardiff.ac.uk
                ewaters@unimelb.edu.au
                MurphyS7@cardiff.ac.uk
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                17 September 2015
                17 September 2015
                2015
                : 15
                : 907
                Affiliations
                [ ]DECIPHer, School of Social Sciences, Cardiff University, 1-3 Museum Place, Cardiff, CF10 3BD UK
                [ ]Jack Brockhoff Child Health and Wellbeing Program, School of Population and Global Health, University of Melbourne, Melbourne, Australia
                Article
                2244
                10.1186/s12889-015-2244-x
                4574356
                d94e6542-01b6-486a-9fed-e00b96846603
                © Moore et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 28 April 2015
                : 7 September 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Public health
                Public health

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